{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "dbc7b1a3",
   "metadata": {},
   "source": [
    "# 0. 环境准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "80ee5229",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "# 设置pandas可以显示的行数和列数\n",
    "pd.options.display.max_rows = 400\n",
    "pd.options.display.max_columns = None\n",
    "\n",
    "# 忽略warnings\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "#推荐安装插件（折叠文本框）： nbextensions  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b2d542e",
   "metadata": {},
   "source": [
    "# 1. 读入数据"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9aac2cbd",
   "metadata": {},
   "source": [
    "## 股价数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1a1001ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>company</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-05-18</td>\n",
       "      <td>FB</td>\n",
       "      <td>38.230000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-05-21</td>\n",
       "      <td>FB</td>\n",
       "      <td>34.029999</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date company      price\n",
       "0 2012-05-18      FB  38.230000\n",
       "1 2012-05-21      FB  34.029999"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# date: 日期\n",
    "# company: 公司代码\n",
    "# price: 股价\n",
    "df_stock = pd.read_csv('./data/stock_price.csv', parse_dates=['date'])\n",
    "df_stock.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1041244d",
   "metadata": {},
   "source": [
    "## 商品销量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4df9fc00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>store</th>\n",
       "      <th>dept</th>\n",
       "      <th>week</th>\n",
       "      <th>sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-01</td>\n",
       "      <td>24924.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-08</td>\n",
       "      <td>46039.49</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   store  dept       week     sales\n",
       "0      1     1 2010-02-01  24924.50\n",
       "1      1     1 2010-02-08  46039.49"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# store:门店编号\n",
    "# dept: 商品部门编号\n",
    "# week: 每周周一的日期 \n",
    "# sales: 销售金额\n",
    "df_sales = pd.read_csv('./data/store_sales.csv', parse_dates=['week'])\n",
    "df_sales.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a0ae496",
   "metadata": {},
   "source": [
    "# 2. 时间序列的可视化"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25655e95",
   "metadata": {},
   "source": [
    "## 简单时序图，用于对时间数据进行初步观察"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86ade6fd",
   "metadata": {},
   "source": [
    "### 股价数据，以FB的股价为例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2c6ef8b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([14975., 15340., 15706., 16071., 16436., 16801., 17167., 17532.,\n",
       "        17897., 18262., 18628., 18993.]),\n",
       " [Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, '')])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 全时序图\n",
    "df = df_stock[ df_stock['company']=='FB' ].sort_values('date')\n",
    "plt.plot( df['date'], df['price'],'.-' )\n",
    "plt.xticks(rotation=90)  # 横轴旋转"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "471449de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 局部时序图\n",
    "df = df_stock[ (df_stock['company']=='FB') & \n",
    "             (df_stock['date']>='2020-01-01') & \n",
    "             (df_stock['date']<='2021-12-31')].sort_values('date')\n",
    "plt.plot( df['date'], df['price'],'.-' )\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f2b6fc4",
   "metadata": {},
   "source": [
    "结论：FB的股价总体呈现上市的趋势，局部有波动"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35dcad23",
   "metadata": {},
   "source": [
    "### 销售数据， 以1号店的1号部门为例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "145131f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 全时序图\n",
    "df = df_sales[ (df_sales['store']==1) & \n",
    "             (df_sales['dept']==1)].sort_values('week')\n",
    "plt.plot( df['week'], df['sales'],'.-' )\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98a3e95d",
   "metadata": {},
   "source": [
    "结论: 1号店1号部门的销售呈现出以1年（既52周）为单位的周期性"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2ef7bde",
   "metadata": {},
   "source": [
    "## 季节性时序图"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c52a816",
   "metadata": {},
   "source": [
    "### 数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e8bc574f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>store</th>\n",
       "      <th>dept</th>\n",
       "      <th>week</th>\n",
       "      <th>sales</th>\n",
       "      <th>year</th>\n",
       "      <th>week_of_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-01</td>\n",
       "      <td>24924.50</td>\n",
       "      <td>2010</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-08</td>\n",
       "      <td>46039.49</td>\n",
       "      <td>2010</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-15</td>\n",
       "      <td>41595.55</td>\n",
       "      <td>2010</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   store  dept       week     sales  year  week_of_year\n",
       "0      1     1 2010-02-01  24924.50  2010             5\n",
       "1      1     1 2010-02-08  46039.49  2010             6\n",
       "2      1     1 2010-02-15  41595.55  2010             7"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 以1号店1号部门的销售数据为例\n",
    "df = df_sales[ (df_sales['store']==1) & \n",
    "             (df_sales['dept']==1)].sort_values('week')\n",
    "\n",
    "#计算每周属于哪一年\n",
    "df['year'] = df['week'].dt.year\n",
    "\n",
    "#计算每周为一年当中的第几周\n",
    "df['week_of_year'] = df['week'].dt.weekofyear\n",
    "\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2138d7f5",
   "metadata": {},
   "source": [
    "### 作图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ed901a00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for year in df['year'].unique():\n",
    "    tmp_df = df[ df['year']==year ]\n",
    "    plt.plot( tmp_df['week_of_year'], tmp_df['sales'],'.-', label=str(year) )\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c883cf7c",
   "metadata": {},
   "source": [
    "结论： \n",
    "1. 每年19周-43周（4-10月）是销售的低估\n",
    "2. 每年44周-次年18周（10-4月）疑似有促销活动\n",
    "3. 趋势上11年略低于10和12年\n",
    "\n",
    "- 12周左右 峰值点不在一起，说明 周期性 不是一个天然的周期性因素，可能是 人为影响（阴历节假日促销活动）"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef956f0c",
   "metadata": {},
   "source": [
    "## 季节性箱线图"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28e6c3f2",
   "metadata": {},
   "source": [
    "### 数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "818eff6d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>week_of_year</th>\n",
       "      <th>sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>[15984.24, 16567.69]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>[17359.7, 16894.4]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>[17341.47, 18365.1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>[18461.18, 18378.16]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>[24924.5, 21665.76, 23510.49]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   week_of_year                          sales\n",
       "0             1           [15984.24, 16567.69]\n",
       "1             2             [17359.7, 16894.4]\n",
       "2             3            [17341.47, 18365.1]\n",
       "3             4           [18461.18, 18378.16]\n",
       "4             5  [24924.5, 21665.76, 23510.49]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 以1号店1号部门的销售数据为例\n",
    "df = df_sales[ (df_sales['store']==1) & \n",
    "             (df_sales['dept']==1)].sort_values('week')\n",
    "\n",
    "#计算每周为一年当中的第几周\n",
    "df['week_of_year'] = df['week'].dt.weekofyear\n",
    "\n",
    "#将一年当中同一周的数据汇集到一个list\n",
    "df_boxplot = df.groupby(['week_of_year'])['sales'].agg(list).reset_index()\n",
    "\n",
    "df_boxplot.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff5be2e0",
   "metadata": {},
   "source": [
    "### 作图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e176960b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot( df_boxplot['sales'].values, labels=df_boxplot['week_of_year'].values )\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2602cd07",
   "metadata": {},
   "source": [
    "## 趋势箱线图"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "827ea3f6",
   "metadata": {},
   "source": [
    "### 数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b3b9df4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>[18926.74, 14773.04, 15580.43, 17558.09, 16637...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011</td>\n",
       "      <td>[17235.15, 15136.78, 15741.6, 16434.15, 15883....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012</td>\n",
       "      <td>[18164.2, 18517.79, 16963.55, 16065.49, 17666....</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year                                              sales\n",
       "0  2010  [18926.74, 14773.04, 15580.43, 17558.09, 16637...\n",
       "1  2011  [17235.15, 15136.78, 15741.6, 16434.15, 15883....\n",
       "2  2012  [18164.2, 18517.79, 16963.55, 16065.49, 17666...."
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 以1号店1号部门的销售数据为例\n",
    "df = df_sales[ (df_sales['store']==1) & \n",
    "             (df_sales['dept']==1)].sort_values('week')\n",
    "\n",
    "#计算每周属于哪一年\n",
    "df['year'] = df['week'].dt.year\n",
    "\n",
    "#计算每周为一年当中的第几周\n",
    "df['week_of_year'] = df['week'].dt.weekofyear\n",
    "\n",
    "#只保留19-43周的数字，因为其他周受促销活动的干扰\n",
    "df = df[ (df['week_of_year']>=19) & \n",
    "       (df['week_of_year']<=43)]\n",
    "\n",
    "#将同一年数据汇集到一个list\n",
    "df_boxplot = df.groupby(['year'])['sales'].agg(list).reset_index()\n",
    "df_boxplot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a95b79d2",
   "metadata": {},
   "source": [
    "### 作图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "27817755",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot( df_boxplot['sales'].values, labels=df_boxplot['year'].values )\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55021e07",
   "metadata": {},
   "source": [
    "# 如何判断周期性"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b57b0945",
   "metadata": {},
   "source": [
    "ACF检验 (Auto-Correlation Function, 自相关系数检验） \n",
    "$$ r_h = Cor( X_t, X_{t+h} ) , \\forall t$$\n",
    "如果每隔h个单位，ACF值有一个局部高峰，则数据存在以h为单位的周期性"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb97fd9e",
   "metadata": {},
   "source": [
    "## 数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "fcf172ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 以1号店1号部门的销售数据为例\n",
    "df = df_sales[ (df_sales['store']==1) & \n",
    "             (df_sales['dept']==1)].sort_values('week')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9bab466",
   "metadata": {},
   "source": [
    "## 计算周期性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a1231e0d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from  statsmodels.graphics.tsaplots import plot_acf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "feffa91b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_acf(df['sales'], lags=140).show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "deafc135",
   "metadata": {},
   "source": [
    "结论：数据存在以52周（1年）为单位的周期性,（两个高点之间的距离）"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ee49974",
   "metadata": {},
   "source": [
    "# 3. 用STL算法分解时间序列"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ff9fc28",
   "metadata": {},
   "source": [
    "## 数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a30d8fbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 以1号店1号部门的销售数据为例\n",
    "df = df_sales[ (df_sales['store']==1) & \n",
    "             (df_sales['dept']==1)].sort_values('week')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03b0ed38",
   "metadata": {},
   "source": [
    "## STL分解"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "037073ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.seasonal import STL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e2ca7d5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "stl = STL(df['sales'].values, period=52) #period: 时间序列的周期\n",
    "res = stl.fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "462a5758",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## 分解结果可视化\n",
    "fig = res.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "61ab8372",
   "metadata": {},
   "outputs": [],
   "source": [
    "## 获取结果数字\n",
    "df['trend'] = res.trend\n",
    "df['seasonal'] = res.seasonal\n",
    "df['residule'] = res.resid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "735416f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>store</th>\n",
       "      <th>dept</th>\n",
       "      <th>week</th>\n",
       "      <th>sales</th>\n",
       "      <th>trend</th>\n",
       "      <th>seasonal</th>\n",
       "      <th>residule</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-01</td>\n",
       "      <td>24924.50</td>\n",
       "      <td>23277.726484</td>\n",
       "      <td>1009.587224</td>\n",
       "      <td>637.186292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-08</td>\n",
       "      <td>46039.49</td>\n",
       "      <td>23264.875227</td>\n",
       "      <td>21817.972147</td>\n",
       "      <td>956.642626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-15</td>\n",
       "      <td>41595.55</td>\n",
       "      <td>23252.134232</td>\n",
       "      <td>18180.173545</td>\n",
       "      <td>163.242223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-02-22</td>\n",
       "      <td>19403.54</td>\n",
       "      <td>23239.503284</td>\n",
       "      <td>-3822.738460</td>\n",
       "      <td>-13.224824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-03-01</td>\n",
       "      <td>21827.90</td>\n",
       "      <td>23226.981632</td>\n",
       "      <td>-1455.928194</td>\n",
       "      <td>56.846562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-03-08</td>\n",
       "      <td>21043.39</td>\n",
       "      <td>23214.568454</td>\n",
       "      <td>-1976.582305</td>\n",
       "      <td>-194.596149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-03-15</td>\n",
       "      <td>22136.64</td>\n",
       "      <td>23202.262889</td>\n",
       "      <td>-1498.156304</td>\n",
       "      <td>432.533415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-03-22</td>\n",
       "      <td>26229.21</td>\n",
       "      <td>23190.064138</td>\n",
       "      <td>2199.918411</td>\n",
       "      <td>839.227451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-03-29</td>\n",
       "      <td>57258.43</td>\n",
       "      <td>23177.970635</td>\n",
       "      <td>27435.396454</td>\n",
       "      <td>6645.062911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-04-05</td>\n",
       "      <td>42960.91</td>\n",
       "      <td>23165.977629</td>\n",
       "      <td>12047.770473</td>\n",
       "      <td>7747.161898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-04-12</td>\n",
       "      <td>17596.96</td>\n",
       "      <td>23154.069754</td>\n",
       "      <td>-4619.294113</td>\n",
       "      <td>-937.815641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-04-19</td>\n",
       "      <td>16145.35</td>\n",
       "      <td>23142.220335</td>\n",
       "      <td>3314.630200</td>\n",
       "      <td>-10311.500535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-04-26</td>\n",
       "      <td>16555.11</td>\n",
       "      <td>23130.403624</td>\n",
       "      <td>1079.944800</td>\n",
       "      <td>-7655.238423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-05-03</td>\n",
       "      <td>17413.94</td>\n",
       "      <td>23118.607348</td>\n",
       "      <td>-4688.978078</td>\n",
       "      <td>-1015.689269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-05-10</td>\n",
       "      <td>18926.74</td>\n",
       "      <td>23106.830873</td>\n",
       "      <td>-4409.574843</td>\n",
       "      <td>229.483970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-05-17</td>\n",
       "      <td>14773.04</td>\n",
       "      <td>23095.076998</td>\n",
       "      <td>-8609.810525</td>\n",
       "      <td>287.773526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-05-24</td>\n",
       "      <td>15580.43</td>\n",
       "      <td>23083.348800</td>\n",
       "      <td>-7497.461643</td>\n",
       "      <td>-5.457157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-05-31</td>\n",
       "      <td>17558.09</td>\n",
       "      <td>23071.649324</td>\n",
       "      <td>-5462.138954</td>\n",
       "      <td>-51.420370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-06-07</td>\n",
       "      <td>16637.62</td>\n",
       "      <td>23059.981915</td>\n",
       "      <td>-6637.364732</td>\n",
       "      <td>215.002817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-06-14</td>\n",
       "      <td>16216.27</td>\n",
       "      <td>23048.350306</td>\n",
       "      <td>-7239.111482</td>\n",
       "      <td>407.031176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-06-21</td>\n",
       "      <td>16328.72</td>\n",
       "      <td>23036.758331</td>\n",
       "      <td>-6783.115358</td>\n",
       "      <td>75.077027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-06-28</td>\n",
       "      <td>16333.14</td>\n",
       "      <td>23025.209756</td>\n",
       "      <td>-6727.715142</td>\n",
       "      <td>35.645386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-07-05</td>\n",
       "      <td>17688.76</td>\n",
       "      <td>23013.708606</td>\n",
       "      <td>-5643.288060</td>\n",
       "      <td>318.339454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-07-12</td>\n",
       "      <td>17150.84</td>\n",
       "      <td>23002.259252</td>\n",
       "      <td>-6049.858660</td>\n",
       "      <td>198.439408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-07-19</td>\n",
       "      <td>15360.45</td>\n",
       "      <td>22990.866193</td>\n",
       "      <td>-7495.915454</td>\n",
       "      <td>-134.500739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-07-26</td>\n",
       "      <td>15381.82</td>\n",
       "      <td>22979.534220</td>\n",
       "      <td>-7328.472235</td>\n",
       "      <td>-269.241985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-08-02</td>\n",
       "      <td>17508.41</td>\n",
       "      <td>22968.268876</td>\n",
       "      <td>-5831.304619</td>\n",
       "      <td>371.445743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-08-09</td>\n",
       "      <td>15536.40</td>\n",
       "      <td>22957.076612</td>\n",
       "      <td>-7648.176908</td>\n",
       "      <td>227.500296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-08-16</td>\n",
       "      <td>15740.13</td>\n",
       "      <td>22945.964267</td>\n",
       "      <td>-7601.157743</td>\n",
       "      <td>395.323475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-08-23</td>\n",
       "      <td>15793.87</td>\n",
       "      <td>22934.939048</td>\n",
       "      <td>-7434.639495</td>\n",
       "      <td>293.570448</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-08-30</td>\n",
       "      <td>16241.78</td>\n",
       "      <td>22924.008445</td>\n",
       "      <td>-6881.327872</td>\n",
       "      <td>199.099428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-09-06</td>\n",
       "      <td>18194.74</td>\n",
       "      <td>22913.180359</td>\n",
       "      <td>-4717.506482</td>\n",
       "      <td>-0.933877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-09-13</td>\n",
       "      <td>19354.23</td>\n",
       "      <td>22902.463347</td>\n",
       "      <td>-3679.186127</td>\n",
       "      <td>130.952780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-09-20</td>\n",
       "      <td>18122.52</td>\n",
       "      <td>22891.866952</td>\n",
       "      <td>-4864.672837</td>\n",
       "      <td>95.325885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-09-27</td>\n",
       "      <td>20094.19</td>\n",
       "      <td>22881.401783</td>\n",
       "      <td>-2989.744184</td>\n",
       "      <td>202.532401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-10-04</td>\n",
       "      <td>23388.03</td>\n",
       "      <td>22871.079685</td>\n",
       "      <td>114.609920</td>\n",
       "      <td>402.340395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-10-11</td>\n",
       "      <td>26978.34</td>\n",
       "      <td>22860.913817</td>\n",
       "      <td>3730.819668</td>\n",
       "      <td>386.606515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-10-18</td>\n",
       "      <td>25543.04</td>\n",
       "      <td>22850.918678</td>\n",
       "      <td>2388.978345</td>\n",
       "      <td>303.142976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-10-25</td>\n",
       "      <td>38640.93</td>\n",
       "      <td>22841.110510</td>\n",
       "      <td>15518.917177</td>\n",
       "      <td>280.902313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-11-01</td>\n",
       "      <td>34238.88</td>\n",
       "      <td>22831.508088</td>\n",
       "      <td>11443.326525</td>\n",
       "      <td>-35.954613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-11-08</td>\n",
       "      <td>19549.39</td>\n",
       "      <td>22822.133945</td>\n",
       "      <td>-3236.468177</td>\n",
       "      <td>-36.275768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-11-15</td>\n",
       "      <td>19552.84</td>\n",
       "      <td>22813.016509</td>\n",
       "      <td>-3223.609775</td>\n",
       "      <td>-36.566734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-11-22</td>\n",
       "      <td>18820.29</td>\n",
       "      <td>22804.192707</td>\n",
       "      <td>-3947.076861</td>\n",
       "      <td>-36.825846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-11-29</td>\n",
       "      <td>22517.56</td>\n",
       "      <td>22795.711417</td>\n",
       "      <td>-241.099273</td>\n",
       "      <td>-37.052144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-12-06</td>\n",
       "      <td>31497.65</td>\n",
       "      <td>22787.637956</td>\n",
       "      <td>8747.257571</td>\n",
       "      <td>-37.245527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-12-13</td>\n",
       "      <td>44912.86</td>\n",
       "      <td>22780.059243</td>\n",
       "      <td>22170.207585</td>\n",
       "      <td>-37.406827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-12-20</td>\n",
       "      <td>55931.23</td>\n",
       "      <td>22773.088096</td>\n",
       "      <td>33195.679734</td>\n",
       "      <td>-37.537830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2010-12-27</td>\n",
       "      <td>19124.58</td>\n",
       "      <td>22766.862563</td>\n",
       "      <td>-3604.641309</td>\n",
       "      <td>-37.641254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>15984.24</td>\n",
       "      <td>22761.531325</td>\n",
       "      <td>-6739.570644</td>\n",
       "      <td>-37.720681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-10</td>\n",
       "      <td>17359.70</td>\n",
       "      <td>22757.208815</td>\n",
       "      <td>-5359.728452</td>\n",
       "      <td>-37.780364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-17</td>\n",
       "      <td>17341.47</td>\n",
       "      <td>22753.876275</td>\n",
       "      <td>-5374.581494</td>\n",
       "      <td>-37.824780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-24</td>\n",
       "      <td>18461.18</td>\n",
       "      <td>22748.689673</td>\n",
       "      <td>-4249.638081</td>\n",
       "      <td>-37.871591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-31</td>\n",
       "      <td>21665.76</td>\n",
       "      <td>22743.261333</td>\n",
       "      <td>366.664422</td>\n",
       "      <td>-1444.165754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-02-07</td>\n",
       "      <td>37887.17</td>\n",
       "      <td>22737.555895</td>\n",
       "      <td>17279.273710</td>\n",
       "      <td>-2129.659605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-02-14</td>\n",
       "      <td>46845.87</td>\n",
       "      <td>22731.541160</td>\n",
       "      <td>24544.516230</td>\n",
       "      <td>-430.187391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-02-21</td>\n",
       "      <td>19363.83</td>\n",
       "      <td>22725.186089</td>\n",
       "      <td>-3308.483692</td>\n",
       "      <td>-52.872397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-02-28</td>\n",
       "      <td>20327.61</td>\n",
       "      <td>22718.462743</td>\n",
       "      <td>-2186.930908</td>\n",
       "      <td>-203.921835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-03-07</td>\n",
       "      <td>21280.40</td>\n",
       "      <td>22711.341639</td>\n",
       "      <td>-1765.000137</td>\n",
       "      <td>334.058498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-03-14</td>\n",
       "      <td>20334.23</td>\n",
       "      <td>22703.787516</td>\n",
       "      <td>-1358.714755</td>\n",
       "      <td>-1010.842761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-03-21</td>\n",
       "      <td>20881.10</td>\n",
       "      <td>22695.787546</td>\n",
       "      <td>68.650184</td>\n",
       "      <td>-1883.337730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-03-28</td>\n",
       "      <td>20398.09</td>\n",
       "      <td>22687.469612</td>\n",
       "      <td>12037.386376</td>\n",
       "      <td>-14326.765988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-04-04</td>\n",
       "      <td>23873.79</td>\n",
       "      <td>22679.162715</td>\n",
       "      <td>17884.232911</td>\n",
       "      <td>-16689.605626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-04-11</td>\n",
       "      <td>28762.37</td>\n",
       "      <td>22671.315928</td>\n",
       "      <td>4168.781621</td>\n",
       "      <td>1922.272451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-04-18</td>\n",
       "      <td>50510.31</td>\n",
       "      <td>22664.347352</td>\n",
       "      <td>5835.847383</td>\n",
       "      <td>22010.115266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-04-25</td>\n",
       "      <td>41512.39</td>\n",
       "      <td>22658.632093</td>\n",
       "      <td>2537.236872</td>\n",
       "      <td>16316.521035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-05-02</td>\n",
       "      <td>20138.19</td>\n",
       "      <td>22654.491950</td>\n",
       "      <td>-4602.624662</td>\n",
       "      <td>2086.322713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-05-09</td>\n",
       "      <td>17235.15</td>\n",
       "      <td>22652.081167</td>\n",
       "      <td>-4833.762402</td>\n",
       "      <td>-583.168765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-05-16</td>\n",
       "      <td>15136.78</td>\n",
       "      <td>22651.317754</td>\n",
       "      <td>-6805.490162</td>\n",
       "      <td>-709.047592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-05-23</td>\n",
       "      <td>15741.60</td>\n",
       "      <td>22651.975495</td>\n",
       "      <td>-6828.791027</td>\n",
       "      <td>-81.584468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-05-30</td>\n",
       "      <td>16434.15</td>\n",
       "      <td>22653.818460</td>\n",
       "      <td>-6235.624565</td>\n",
       "      <td>15.956104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-06-06</td>\n",
       "      <td>15883.52</td>\n",
       "      <td>22656.645615</td>\n",
       "      <td>-6217.142852</td>\n",
       "      <td>-555.982764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-06-13</td>\n",
       "      <td>14978.09</td>\n",
       "      <td>22660.292783</td>\n",
       "      <td>-6713.713740</td>\n",
       "      <td>-968.489042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-06-20</td>\n",
       "      <td>15682.81</td>\n",
       "      <td>22664.621945</td>\n",
       "      <td>-6723.761711</td>\n",
       "      <td>-258.050234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-06-27</td>\n",
       "      <td>15363.50</td>\n",
       "      <td>22669.517113</td>\n",
       "      <td>-7131.494081</td>\n",
       "      <td>-174.523032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-07-04</td>\n",
       "      <td>16148.87</td>\n",
       "      <td>22674.886825</td>\n",
       "      <td>-5744.664461</td>\n",
       "      <td>-781.352364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-07-11</td>\n",
       "      <td>15654.85</td>\n",
       "      <td>22680.660614</td>\n",
       "      <td>-6500.418407</td>\n",
       "      <td>-525.392207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-07-18</td>\n",
       "      <td>15766.60</td>\n",
       "      <td>22686.776297</td>\n",
       "      <td>-7107.291184</td>\n",
       "      <td>187.114886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-07-25</td>\n",
       "      <td>15922.41</td>\n",
       "      <td>22693.173205</td>\n",
       "      <td>-7245.587247</td>\n",
       "      <td>474.824042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-08-01</td>\n",
       "      <td>15295.55</td>\n",
       "      <td>22699.798074</td>\n",
       "      <td>-6504.893091</td>\n",
       "      <td>-899.354983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-08-08</td>\n",
       "      <td>14539.79</td>\n",
       "      <td>22706.601381</td>\n",
       "      <td>-7574.788534</td>\n",
       "      <td>-592.022847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-08-15</td>\n",
       "      <td>14689.24</td>\n",
       "      <td>22713.536562</td>\n",
       "      <td>-7071.442244</td>\n",
       "      <td>-952.854318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-08-22</td>\n",
       "      <td>14537.37</td>\n",
       "      <td>22720.559216</td>\n",
       "      <td>-7447.229390</td>\n",
       "      <td>-735.959826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-08-29</td>\n",
       "      <td>15277.27</td>\n",
       "      <td>22727.633347</td>\n",
       "      <td>-6915.696396</td>\n",
       "      <td>-534.666951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-09-05</td>\n",
       "      <td>17746.68</td>\n",
       "      <td>22734.726718</td>\n",
       "      <td>-4880.917955</td>\n",
       "      <td>-107.128763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-09-12</td>\n",
       "      <td>18535.48</td>\n",
       "      <td>22741.810207</td>\n",
       "      <td>-3815.425745</td>\n",
       "      <td>-390.904462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-09-19</td>\n",
       "      <td>17859.30</td>\n",
       "      <td>22748.853939</td>\n",
       "      <td>-4573.909339</td>\n",
       "      <td>-315.644600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-09-26</td>\n",
       "      <td>18337.68</td>\n",
       "      <td>22755.826949</td>\n",
       "      <td>-3871.702751</td>\n",
       "      <td>-546.444198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-10-03</td>\n",
       "      <td>20797.58</td>\n",
       "      <td>22762.699100</td>\n",
       "      <td>-989.477575</td>\n",
       "      <td>-975.641525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-10-10</td>\n",
       "      <td>23077.55</td>\n",
       "      <td>22769.445715</td>\n",
       "      <td>1250.950131</td>\n",
       "      <td>-942.845846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-10-17</td>\n",
       "      <td>23351.80</td>\n",
       "      <td>22776.050428</td>\n",
       "      <td>1340.578075</td>\n",
       "      <td>-764.828503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-10-24</td>\n",
       "      <td>31579.90</td>\n",
       "      <td>22782.507799</td>\n",
       "      <td>9515.335266</td>\n",
       "      <td>-717.943064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-10-31</td>\n",
       "      <td>39886.06</td>\n",
       "      <td>22788.822138</td>\n",
       "      <td>17136.821216</td>\n",
       "      <td>-39.583354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-11-07</td>\n",
       "      <td>18689.54</td>\n",
       "      <td>22795.005790</td>\n",
       "      <td>-4065.960329</td>\n",
       "      <td>-39.505461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-11-14</td>\n",
       "      <td>19050.66</td>\n",
       "      <td>22802.523373</td>\n",
       "      <td>-3712.446191</td>\n",
       "      <td>-39.417182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-11-21</td>\n",
       "      <td>20911.25</td>\n",
       "      <td>22811.170886</td>\n",
       "      <td>-1860.618519</td>\n",
       "      <td>-39.302367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-11-28</td>\n",
       "      <td>25293.49</td>\n",
       "      <td>22820.770691</td>\n",
       "      <td>2511.878175</td>\n",
       "      <td>-39.158866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-12-05</td>\n",
       "      <td>33305.92</td>\n",
       "      <td>22831.118854</td>\n",
       "      <td>10513.786387</td>\n",
       "      <td>-38.985241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-12-12</td>\n",
       "      <td>45773.03</td>\n",
       "      <td>22842.041324</td>\n",
       "      <td>22969.769765</td>\n",
       "      <td>-38.781089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-12-19</td>\n",
       "      <td>46788.75</td>\n",
       "      <td>22853.407203</td>\n",
       "      <td>23973.889848</td>\n",
       "      <td>-38.547050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-12-26</td>\n",
       "      <td>23350.88</td>\n",
       "      <td>22865.124162</td>\n",
       "      <td>524.040511</td>\n",
       "      <td>-38.284673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-01-02</td>\n",
       "      <td>16567.69</td>\n",
       "      <td>22877.129020</td>\n",
       "      <td>-6271.442800</td>\n",
       "      <td>-37.996220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-01-09</td>\n",
       "      <td>16894.40</td>\n",
       "      <td>22889.378839</td>\n",
       "      <td>-5957.294363</td>\n",
       "      <td>-37.684476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-01-16</td>\n",
       "      <td>18365.10</td>\n",
       "      <td>22901.844071</td>\n",
       "      <td>-4499.391520</td>\n",
       "      <td>-37.352550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-01-23</td>\n",
       "      <td>18378.16</td>\n",
       "      <td>22914.503774</td>\n",
       "      <td>-4499.340066</td>\n",
       "      <td>-37.003708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-01-30</td>\n",
       "      <td>23510.49</td>\n",
       "      <td>22927.342453</td>\n",
       "      <td>-36.390241</td>\n",
       "      <td>619.537788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-02-06</td>\n",
       "      <td>36988.49</td>\n",
       "      <td>22940.347798</td>\n",
       "      <td>13108.382572</td>\n",
       "      <td>939.759630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-02-13</td>\n",
       "      <td>54060.10</td>\n",
       "      <td>22953.508503</td>\n",
       "      <td>30959.455025</td>\n",
       "      <td>147.136472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-02-20</td>\n",
       "      <td>20124.22</td>\n",
       "      <td>22966.813406</td>\n",
       "      <td>-2814.049236</td>\n",
       "      <td>-28.544170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-02-27</td>\n",
       "      <td>20113.03</td>\n",
       "      <td>22980.252262</td>\n",
       "      <td>-2909.542734</td>\n",
       "      <td>42.320472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-03-05</td>\n",
       "      <td>21140.07</td>\n",
       "      <td>22993.815911</td>\n",
       "      <td>-1645.421774</td>\n",
       "      <td>-208.324137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-03-12</td>\n",
       "      <td>22366.88</td>\n",
       "      <td>23007.496088</td>\n",
       "      <td>-1060.222786</td>\n",
       "      <td>419.606698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-03-19</td>\n",
       "      <td>22107.70</td>\n",
       "      <td>23021.285343</td>\n",
       "      <td>-1740.689185</td>\n",
       "      <td>827.103842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-03-26</td>\n",
       "      <td>28952.86</td>\n",
       "      <td>23035.176197</td>\n",
       "      <td>-716.059432</td>\n",
       "      <td>6633.743236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-04-02</td>\n",
       "      <td>57592.12</td>\n",
       "      <td>23049.159015</td>\n",
       "      <td>26806.314715</td>\n",
       "      <td>7736.646271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-04-09</td>\n",
       "      <td>34684.21</td>\n",
       "      <td>23063.215963</td>\n",
       "      <td>12568.521631</td>\n",
       "      <td>-947.527594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-04-16</td>\n",
       "      <td>16976.19</td>\n",
       "      <td>23077.321919</td>\n",
       "      <td>4219.277633</td>\n",
       "      <td>-10320.409552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-04-23</td>\n",
       "      <td>16347.60</td>\n",
       "      <td>23091.456380</td>\n",
       "      <td>919.489225</td>\n",
       "      <td>-7663.345605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-04-30</td>\n",
       "      <td>17147.44</td>\n",
       "      <td>23105.613688</td>\n",
       "      <td>-4935.125766</td>\n",
       "      <td>-1023.047922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-05-07</td>\n",
       "      <td>18164.20</td>\n",
       "      <td>23119.799301</td>\n",
       "      <td>-5178.468366</td>\n",
       "      <td>222.869065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-05-14</td>\n",
       "      <td>18517.79</td>\n",
       "      <td>23134.021137</td>\n",
       "      <td>-4898.133803</td>\n",
       "      <td>281.902666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-05-21</td>\n",
       "      <td>16963.55</td>\n",
       "      <td>23148.286535</td>\n",
       "      <td>-6174.154345</td>\n",
       "      <td>-10.582191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-05-28</td>\n",
       "      <td>16065.49</td>\n",
       "      <td>23162.602057</td>\n",
       "      <td>-7041.313732</td>\n",
       "      <td>-55.798325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-06-04</td>\n",
       "      <td>17666.00</td>\n",
       "      <td>23176.973856</td>\n",
       "      <td>-5722.345915</td>\n",
       "      <td>211.372059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-06-11</td>\n",
       "      <td>17558.82</td>\n",
       "      <td>23191.407781</td>\n",
       "      <td>-6036.734402</td>\n",
       "      <td>404.146621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-06-18</td>\n",
       "      <td>16633.41</td>\n",
       "      <td>23205.909105</td>\n",
       "      <td>-6645.435943</td>\n",
       "      <td>72.936838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-06-25</td>\n",
       "      <td>15722.82</td>\n",
       "      <td>23220.482397</td>\n",
       "      <td>-7531.909681</td>\n",
       "      <td>34.247284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-07-02</td>\n",
       "      <td>17823.37</td>\n",
       "      <td>23235.131864</td>\n",
       "      <td>-5729.443219</td>\n",
       "      <td>317.681355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-07-09</td>\n",
       "      <td>16566.18</td>\n",
       "      <td>23249.861419</td>\n",
       "      <td>-6882.201990</td>\n",
       "      <td>198.520571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-07-16</td>\n",
       "      <td>16348.06</td>\n",
       "      <td>23264.674445</td>\n",
       "      <td>-6782.937005</td>\n",
       "      <td>-133.677440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-07-23</td>\n",
       "      <td>15731.18</td>\n",
       "      <td>23279.573955</td>\n",
       "      <td>-7280.728001</td>\n",
       "      <td>-267.665955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-07-30</td>\n",
       "      <td>16628.31</td>\n",
       "      <td>23294.563028</td>\n",
       "      <td>-7040.050400</td>\n",
       "      <td>373.797373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-08-06</td>\n",
       "      <td>16119.92</td>\n",
       "      <td>23309.644854</td>\n",
       "      <td>-7420.364749</td>\n",
       "      <td>230.639895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-08-13</td>\n",
       "      <td>17330.70</td>\n",
       "      <td>23324.822116</td>\n",
       "      <td>-6393.372845</td>\n",
       "      <td>399.250729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-08-20</td>\n",
       "      <td>16286.40</td>\n",
       "      <td>23340.096938</td>\n",
       "      <td>-7351.979707</td>\n",
       "      <td>298.282768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-08-27</td>\n",
       "      <td>16680.24</td>\n",
       "      <td>23355.470773</td>\n",
       "      <td>-6879.822291</td>\n",
       "      <td>204.591518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-09-03</td>\n",
       "      <td>18322.37</td>\n",
       "      <td>23370.944515</td>\n",
       "      <td>-5053.904086</td>\n",
       "      <td>5.329571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-09-10</td>\n",
       "      <td>19616.22</td>\n",
       "      <td>23386.518703</td>\n",
       "      <td>-3908.274461</td>\n",
       "      <td>137.975758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-09-17</td>\n",
       "      <td>19251.50</td>\n",
       "      <td>23402.193755</td>\n",
       "      <td>-4253.786792</td>\n",
       "      <td>103.093037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-09-24</td>\n",
       "      <td>18947.81</td>\n",
       "      <td>23417.969880</td>\n",
       "      <td>-4681.184883</td>\n",
       "      <td>211.025003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-10-01</td>\n",
       "      <td>21904.47</td>\n",
       "      <td>23433.847059</td>\n",
       "      <td>-1940.913881</td>\n",
       "      <td>411.536822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-10-08</td>\n",
       "      <td>22764.01</td>\n",
       "      <td>23449.824859</td>\n",
       "      <td>-1082.297768</td>\n",
       "      <td>396.482909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-10-15</td>\n",
       "      <td>24185.27</td>\n",
       "      <td>23465.902162</td>\n",
       "      <td>405.694045</td>\n",
       "      <td>313.673793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2012-10-22</td>\n",
       "      <td>27390.81</td>\n",
       "      <td>23482.077156</td>\n",
       "      <td>3616.672371</td>\n",
       "      <td>292.060473</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     store  dept       week     sales         trend      seasonal  \\\n",
       "0        1     1 2010-02-01  24924.50  23277.726484   1009.587224   \n",
       "1        1     1 2010-02-08  46039.49  23264.875227  21817.972147   \n",
       "2        1     1 2010-02-15  41595.55  23252.134232  18180.173545   \n",
       "3        1     1 2010-02-22  19403.54  23239.503284  -3822.738460   \n",
       "4        1     1 2010-03-01  21827.90  23226.981632  -1455.928194   \n",
       "5        1     1 2010-03-08  21043.39  23214.568454  -1976.582305   \n",
       "6        1     1 2010-03-15  22136.64  23202.262889  -1498.156304   \n",
       "7        1     1 2010-03-22  26229.21  23190.064138   2199.918411   \n",
       "8        1     1 2010-03-29  57258.43  23177.970635  27435.396454   \n",
       "9        1     1 2010-04-05  42960.91  23165.977629  12047.770473   \n",
       "10       1     1 2010-04-12  17596.96  23154.069754  -4619.294113   \n",
       "11       1     1 2010-04-19  16145.35  23142.220335   3314.630200   \n",
       "12       1     1 2010-04-26  16555.11  23130.403624   1079.944800   \n",
       "13       1     1 2010-05-03  17413.94  23118.607348  -4688.978078   \n",
       "14       1     1 2010-05-10  18926.74  23106.830873  -4409.574843   \n",
       "15       1     1 2010-05-17  14773.04  23095.076998  -8609.810525   \n",
       "16       1     1 2010-05-24  15580.43  23083.348800  -7497.461643   \n",
       "17       1     1 2010-05-31  17558.09  23071.649324  -5462.138954   \n",
       "18       1     1 2010-06-07  16637.62  23059.981915  -6637.364732   \n",
       "19       1     1 2010-06-14  16216.27  23048.350306  -7239.111482   \n",
       "20       1     1 2010-06-21  16328.72  23036.758331  -6783.115358   \n",
       "21       1     1 2010-06-28  16333.14  23025.209756  -6727.715142   \n",
       "22       1     1 2010-07-05  17688.76  23013.708606  -5643.288060   \n",
       "23       1     1 2010-07-12  17150.84  23002.259252  -6049.858660   \n",
       "24       1     1 2010-07-19  15360.45  22990.866193  -7495.915454   \n",
       "25       1     1 2010-07-26  15381.82  22979.534220  -7328.472235   \n",
       "26       1     1 2010-08-02  17508.41  22968.268876  -5831.304619   \n",
       "27       1     1 2010-08-09  15536.40  22957.076612  -7648.176908   \n",
       "28       1     1 2010-08-16  15740.13  22945.964267  -7601.157743   \n",
       "29       1     1 2010-08-23  15793.87  22934.939048  -7434.639495   \n",
       "30       1     1 2010-08-30  16241.78  22924.008445  -6881.327872   \n",
       "31       1     1 2010-09-06  18194.74  22913.180359  -4717.506482   \n",
       "32       1     1 2010-09-13  19354.23  22902.463347  -3679.186127   \n",
       "33       1     1 2010-09-20  18122.52  22891.866952  -4864.672837   \n",
       "34       1     1 2010-09-27  20094.19  22881.401783  -2989.744184   \n",
       "35       1     1 2010-10-04  23388.03  22871.079685    114.609920   \n",
       "36       1     1 2010-10-11  26978.34  22860.913817   3730.819668   \n",
       "37       1     1 2010-10-18  25543.04  22850.918678   2388.978345   \n",
       "38       1     1 2010-10-25  38640.93  22841.110510  15518.917177   \n",
       "39       1     1 2010-11-01  34238.88  22831.508088  11443.326525   \n",
       "40       1     1 2010-11-08  19549.39  22822.133945  -3236.468177   \n",
       "41       1     1 2010-11-15  19552.84  22813.016509  -3223.609775   \n",
       "42       1     1 2010-11-22  18820.29  22804.192707  -3947.076861   \n",
       "43       1     1 2010-11-29  22517.56  22795.711417   -241.099273   \n",
       "44       1     1 2010-12-06  31497.65  22787.637956   8747.257571   \n",
       "45       1     1 2010-12-13  44912.86  22780.059243  22170.207585   \n",
       "46       1     1 2010-12-20  55931.23  22773.088096  33195.679734   \n",
       "47       1     1 2010-12-27  19124.58  22766.862563  -3604.641309   \n",
       "48       1     1 2011-01-03  15984.24  22761.531325  -6739.570644   \n",
       "49       1     1 2011-01-10  17359.70  22757.208815  -5359.728452   \n",
       "50       1     1 2011-01-17  17341.47  22753.876275  -5374.581494   \n",
       "51       1     1 2011-01-24  18461.18  22748.689673  -4249.638081   \n",
       "52       1     1 2011-01-31  21665.76  22743.261333    366.664422   \n",
       "53       1     1 2011-02-07  37887.17  22737.555895  17279.273710   \n",
       "54       1     1 2011-02-14  46845.87  22731.541160  24544.516230   \n",
       "55       1     1 2011-02-21  19363.83  22725.186089  -3308.483692   \n",
       "56       1     1 2011-02-28  20327.61  22718.462743  -2186.930908   \n",
       "57       1     1 2011-03-07  21280.40  22711.341639  -1765.000137   \n",
       "58       1     1 2011-03-14  20334.23  22703.787516  -1358.714755   \n",
       "59       1     1 2011-03-21  20881.10  22695.787546     68.650184   \n",
       "60       1     1 2011-03-28  20398.09  22687.469612  12037.386376   \n",
       "61       1     1 2011-04-04  23873.79  22679.162715  17884.232911   \n",
       "62       1     1 2011-04-11  28762.37  22671.315928   4168.781621   \n",
       "63       1     1 2011-04-18  50510.31  22664.347352   5835.847383   \n",
       "64       1     1 2011-04-25  41512.39  22658.632093   2537.236872   \n",
       "65       1     1 2011-05-02  20138.19  22654.491950  -4602.624662   \n",
       "66       1     1 2011-05-09  17235.15  22652.081167  -4833.762402   \n",
       "67       1     1 2011-05-16  15136.78  22651.317754  -6805.490162   \n",
       "68       1     1 2011-05-23  15741.60  22651.975495  -6828.791027   \n",
       "69       1     1 2011-05-30  16434.15  22653.818460  -6235.624565   \n",
       "70       1     1 2011-06-06  15883.52  22656.645615  -6217.142852   \n",
       "71       1     1 2011-06-13  14978.09  22660.292783  -6713.713740   \n",
       "72       1     1 2011-06-20  15682.81  22664.621945  -6723.761711   \n",
       "73       1     1 2011-06-27  15363.50  22669.517113  -7131.494081   \n",
       "74       1     1 2011-07-04  16148.87  22674.886825  -5744.664461   \n",
       "75       1     1 2011-07-11  15654.85  22680.660614  -6500.418407   \n",
       "76       1     1 2011-07-18  15766.60  22686.776297  -7107.291184   \n",
       "77       1     1 2011-07-25  15922.41  22693.173205  -7245.587247   \n",
       "78       1     1 2011-08-01  15295.55  22699.798074  -6504.893091   \n",
       "79       1     1 2011-08-08  14539.79  22706.601381  -7574.788534   \n",
       "80       1     1 2011-08-15  14689.24  22713.536562  -7071.442244   \n",
       "81       1     1 2011-08-22  14537.37  22720.559216  -7447.229390   \n",
       "82       1     1 2011-08-29  15277.27  22727.633347  -6915.696396   \n",
       "83       1     1 2011-09-05  17746.68  22734.726718  -4880.917955   \n",
       "84       1     1 2011-09-12  18535.48  22741.810207  -3815.425745   \n",
       "85       1     1 2011-09-19  17859.30  22748.853939  -4573.909339   \n",
       "86       1     1 2011-09-26  18337.68  22755.826949  -3871.702751   \n",
       "87       1     1 2011-10-03  20797.58  22762.699100   -989.477575   \n",
       "88       1     1 2011-10-10  23077.55  22769.445715   1250.950131   \n",
       "89       1     1 2011-10-17  23351.80  22776.050428   1340.578075   \n",
       "90       1     1 2011-10-24  31579.90  22782.507799   9515.335266   \n",
       "91       1     1 2011-10-31  39886.06  22788.822138  17136.821216   \n",
       "92       1     1 2011-11-07  18689.54  22795.005790  -4065.960329   \n",
       "93       1     1 2011-11-14  19050.66  22802.523373  -3712.446191   \n",
       "94       1     1 2011-11-21  20911.25  22811.170886  -1860.618519   \n",
       "95       1     1 2011-11-28  25293.49  22820.770691   2511.878175   \n",
       "96       1     1 2011-12-05  33305.92  22831.118854  10513.786387   \n",
       "97       1     1 2011-12-12  45773.03  22842.041324  22969.769765   \n",
       "98       1     1 2011-12-19  46788.75  22853.407203  23973.889848   \n",
       "99       1     1 2011-12-26  23350.88  22865.124162    524.040511   \n",
       "100      1     1 2012-01-02  16567.69  22877.129020  -6271.442800   \n",
       "101      1     1 2012-01-09  16894.40  22889.378839  -5957.294363   \n",
       "102      1     1 2012-01-16  18365.10  22901.844071  -4499.391520   \n",
       "103      1     1 2012-01-23  18378.16  22914.503774  -4499.340066   \n",
       "104      1     1 2012-01-30  23510.49  22927.342453    -36.390241   \n",
       "105      1     1 2012-02-06  36988.49  22940.347798  13108.382572   \n",
       "106      1     1 2012-02-13  54060.10  22953.508503  30959.455025   \n",
       "107      1     1 2012-02-20  20124.22  22966.813406  -2814.049236   \n",
       "108      1     1 2012-02-27  20113.03  22980.252262  -2909.542734   \n",
       "109      1     1 2012-03-05  21140.07  22993.815911  -1645.421774   \n",
       "110      1     1 2012-03-12  22366.88  23007.496088  -1060.222786   \n",
       "111      1     1 2012-03-19  22107.70  23021.285343  -1740.689185   \n",
       "112      1     1 2012-03-26  28952.86  23035.176197   -716.059432   \n",
       "113      1     1 2012-04-02  57592.12  23049.159015  26806.314715   \n",
       "114      1     1 2012-04-09  34684.21  23063.215963  12568.521631   \n",
       "115      1     1 2012-04-16  16976.19  23077.321919   4219.277633   \n",
       "116      1     1 2012-04-23  16347.60  23091.456380    919.489225   \n",
       "117      1     1 2012-04-30  17147.44  23105.613688  -4935.125766   \n",
       "118      1     1 2012-05-07  18164.20  23119.799301  -5178.468366   \n",
       "119      1     1 2012-05-14  18517.79  23134.021137  -4898.133803   \n",
       "120      1     1 2012-05-21  16963.55  23148.286535  -6174.154345   \n",
       "121      1     1 2012-05-28  16065.49  23162.602057  -7041.313732   \n",
       "122      1     1 2012-06-04  17666.00  23176.973856  -5722.345915   \n",
       "123      1     1 2012-06-11  17558.82  23191.407781  -6036.734402   \n",
       "124      1     1 2012-06-18  16633.41  23205.909105  -6645.435943   \n",
       "125      1     1 2012-06-25  15722.82  23220.482397  -7531.909681   \n",
       "126      1     1 2012-07-02  17823.37  23235.131864  -5729.443219   \n",
       "127      1     1 2012-07-09  16566.18  23249.861419  -6882.201990   \n",
       "128      1     1 2012-07-16  16348.06  23264.674445  -6782.937005   \n",
       "129      1     1 2012-07-23  15731.18  23279.573955  -7280.728001   \n",
       "130      1     1 2012-07-30  16628.31  23294.563028  -7040.050400   \n",
       "131      1     1 2012-08-06  16119.92  23309.644854  -7420.364749   \n",
       "132      1     1 2012-08-13  17330.70  23324.822116  -6393.372845   \n",
       "133      1     1 2012-08-20  16286.40  23340.096938  -7351.979707   \n",
       "134      1     1 2012-08-27  16680.24  23355.470773  -6879.822291   \n",
       "135      1     1 2012-09-03  18322.37  23370.944515  -5053.904086   \n",
       "136      1     1 2012-09-10  19616.22  23386.518703  -3908.274461   \n",
       "137      1     1 2012-09-17  19251.50  23402.193755  -4253.786792   \n",
       "138      1     1 2012-09-24  18947.81  23417.969880  -4681.184883   \n",
       "139      1     1 2012-10-01  21904.47  23433.847059  -1940.913881   \n",
       "140      1     1 2012-10-08  22764.01  23449.824859  -1082.297768   \n",
       "141      1     1 2012-10-15  24185.27  23465.902162    405.694045   \n",
       "142      1     1 2012-10-22  27390.81  23482.077156   3616.672371   \n",
       "\n",
       "         residule  \n",
       "0      637.186292  \n",
       "1      956.642626  \n",
       "2      163.242223  \n",
       "3      -13.224824  \n",
       "4       56.846562  \n",
       "5     -194.596149  \n",
       "6      432.533415  \n",
       "7      839.227451  \n",
       "8     6645.062911  \n",
       "9     7747.161898  \n",
       "10    -937.815641  \n",
       "11  -10311.500535  \n",
       "12   -7655.238423  \n",
       "13   -1015.689269  \n",
       "14     229.483970  \n",
       "15     287.773526  \n",
       "16      -5.457157  \n",
       "17     -51.420370  \n",
       "18     215.002817  \n",
       "19     407.031176  \n",
       "20      75.077027  \n",
       "21      35.645386  \n",
       "22     318.339454  \n",
       "23     198.439408  \n",
       "24    -134.500739  \n",
       "25    -269.241985  \n",
       "26     371.445743  \n",
       "27     227.500296  \n",
       "28     395.323475  \n",
       "29     293.570448  \n",
       "30     199.099428  \n",
       "31      -0.933877  \n",
       "32     130.952780  \n",
       "33      95.325885  \n",
       "34     202.532401  \n",
       "35     402.340395  \n",
       "36     386.606515  \n",
       "37     303.142976  \n",
       "38     280.902313  \n",
       "39     -35.954613  \n",
       "40     -36.275768  \n",
       "41     -36.566734  \n",
       "42     -36.825846  \n",
       "43     -37.052144  \n",
       "44     -37.245527  \n",
       "45     -37.406827  \n",
       "46     -37.537830  \n",
       "47     -37.641254  \n",
       "48     -37.720681  \n",
       "49     -37.780364  \n",
       "50     -37.824780  \n",
       "51     -37.871591  \n",
       "52   -1444.165754  \n",
       "53   -2129.659605  \n",
       "54    -430.187391  \n",
       "55     -52.872397  \n",
       "56    -203.921835  \n",
       "57     334.058498  \n",
       "58   -1010.842761  \n",
       "59   -1883.337730  \n",
       "60  -14326.765988  \n",
       "61  -16689.605626  \n",
       "62    1922.272451  \n",
       "63   22010.115266  \n",
       "64   16316.521035  \n",
       "65    2086.322713  \n",
       "66    -583.168765  \n",
       "67    -709.047592  \n",
       "68     -81.584468  \n",
       "69      15.956104  \n",
       "70    -555.982764  \n",
       "71    -968.489042  \n",
       "72    -258.050234  \n",
       "73    -174.523032  \n",
       "74    -781.352364  \n",
       "75    -525.392207  \n",
       "76     187.114886  \n",
       "77     474.824042  \n",
       "78    -899.354983  \n",
       "79    -592.022847  \n",
       "80    -952.854318  \n",
       "81    -735.959826  \n",
       "82    -534.666951  \n",
       "83    -107.128763  \n",
       "84    -390.904462  \n",
       "85    -315.644600  \n",
       "86    -546.444198  \n",
       "87    -975.641525  \n",
       "88    -942.845846  \n",
       "89    -764.828503  \n",
       "90    -717.943064  \n",
       "91     -39.583354  \n",
       "92     -39.505461  \n",
       "93     -39.417182  \n",
       "94     -39.302367  \n",
       "95     -39.158866  \n",
       "96     -38.985241  \n",
       "97     -38.781089  \n",
       "98     -38.547050  \n",
       "99     -38.284673  \n",
       "100    -37.996220  \n",
       "101    -37.684476  \n",
       "102    -37.352550  \n",
       "103    -37.003708  \n",
       "104    619.537788  \n",
       "105    939.759630  \n",
       "106    147.136472  \n",
       "107    -28.544170  \n",
       "108     42.320472  \n",
       "109   -208.324137  \n",
       "110    419.606698  \n",
       "111    827.103842  \n",
       "112   6633.743236  \n",
       "113   7736.646271  \n",
       "114   -947.527594  \n",
       "115 -10320.409552  \n",
       "116  -7663.345605  \n",
       "117  -1023.047922  \n",
       "118    222.869065  \n",
       "119    281.902666  \n",
       "120    -10.582191  \n",
       "121    -55.798325  \n",
       "122    211.372059  \n",
       "123    404.146621  \n",
       "124     72.936838  \n",
       "125     34.247284  \n",
       "126    317.681355  \n",
       "127    198.520571  \n",
       "128   -133.677440  \n",
       "129   -267.665955  \n",
       "130    373.797373  \n",
       "131    230.639895  \n",
       "132    399.250729  \n",
       "133    298.282768  \n",
       "134    204.591518  \n",
       "135      5.329571  \n",
       "136    137.975758  \n",
       "137    103.093037  \n",
       "138    211.025003  \n",
       "139    411.536822  \n",
       "140    396.482909  \n",
       "141    313.673793  \n",
       "142    292.060473  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35883900",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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